mhahsler/dbscan: Density Based Clustering of Applications with Noise (DBSCAN) and Related Algorithms
Version 1.1-1

A fast reimplementation of several density-based algorithms of the DBSCAN family for spatial data. Includes the DBSCAN (density-based spatial clustering of applications with noise) and OPTICS (ordering points to identify the clustering structure) clustering algorithms HDBSCAN (hierarchical DBSCAN) and the LOF (local outlier factor) algorithm. The implementations use the kd-tree data structure (from library ANN) for faster k-nearest neighbor search. An R interface to fast kNN and fixed-radius NN search is also provided.

Getting started

Package details

Maintainer
LicenseGPL (>= 2)
Version1.1-1
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("mhahsler/dbscan")
mhahsler/dbscan documentation built on Nov. 9, 2017, 4:20 p.m.